Aiman Awan’s Post

I am happy to announce that I have completed the course "Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization" on Coursera. Main topics: open the deep learning black box to understand the processes that drive performance and generate good results systematically; best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. ------------ Description of all modules: Pratical Aspects of Deep Learning: discover and experiment with a variety of different initialization methods, apply L2 regularization and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model. Optimization Algorithms: develop your deep learning toolbox by adding more advanced optimizations, random minibatching, and learning rate decay scheduling to speed up your models. Hyperparameter Tuning, Batch Normalization and Programming Frameworks: explore TensorFlow, a deep learning framework that allows you to build neural networks quickly and easily, then train a neural network on a TensorFlow dataset. Thank you DeepLearning.AI for offering this course. #NeuralNetworks #DeepLearning #Python #TensorFlow #OptimizationAlgorithms

Hi all, I'm excited to share that I have completed the "Introduction to Neural Networks and Deep Learning" course Great Learning Academy offers! 🎉 This course has provided me with a solid foundation in the principles of neural networks and deep learning. I’m looking forward to applying these skills to real-world challenges in artificial intelligence. A big thank you to Great Learning Academy for this valuable learning opportunity! 🙏 #GreatLearningAcademy #greatlearning #glacertificate #NeuralNetworks #DeepLearning #AI #MachineLearning #ContinuousLearning

I'm thrilled to announce that I've just completed IBM's "Introduction to Deep Learning & Neural Networks with Keras"! This in-depth program gave me a solid grasp of Deep Learning using the Keras library. Throughout the course, I explored the workings of Neurons and Neural Networks, Artificial Neural Networks, Gradient Descent, Backpropagation, and Activation Functions. I also learned about Supervised Learning models such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), as well as Unsupervised Learning models like Autoencoders. This course is a major milestone in my journey to mastering Machine Learning and Deep Learning. #DeepLearning #AI #Keras #IBM

I recently completed the Neural Networks and Deep Learning course on Coursera, and it was an incredible! The course provided a comprehensive dive into the world of neural networks, covering everything from the basics to the intricacies of training deep learning models. Throughout the course, I gained a solid understanding of how neural networks function and the various techniques used to optimize them. The hands-on projects and practical examples were particularly beneficial, allowing me to apply theoretical concepts to real-world problems. One of the highlights was learning about different activation functions, loss functions, and optimization algorithms. These insights have greatly enhanced my ability to design and train effective deep learning models. Overall, the experience was immensely rewarding, and I am excited to continue exploring the fascinating field of deep learning.

Two months ago, I only had a vague idea of how neural networks were constructed and used. After this course, I've been able to create a full transformer model and I am super proud of this achievement that required hours of work, watching videos, and hands-on labs practicing. If you strive to learn and be curious like me, I can only recommend this course to understand better the world of deep learning.

Excited to Share My Latest Achievement! I am happy to share that I have successfully completed the "Neural Networks and Deep Learning" course on Coursera. This course has deepened my understanding of the key trends driving the rise of deep learning and its application in various fields. Key Learning Objectives: Analyzed the major trends contributing to the growth of deep learning. Developed deep neural networks with multiple hidden layers for binary image classification. Explored the application of deep learning to supervised learning. Studied the major categories of models (CNNs, RNNs, etc.) and their appropriate use cases. Evaluated suitable scenarios for the application of deep learning techniques. I am excited to apply this knowledge and continue contributing to the advancements in AI and machine learning.

Hi Linkers, I have successfully completed the "Introduction to Neural Networks and Deep Learning" course offered by Great Learning Academy. This course provides an in-depth exploration of the fundamentals and advanced concepts in neural networks and deep learning. hashtag #GreatLearningAcademy hashtag #greatlearning hashtag #glacertificate

An absolutely amazing course that taught me the foundational concept of neural networks and deep learning. Below are the concluding pointers from this course. ➛ With the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network's architecture; and apply deep learning to my own applications. ➛ Setting up a machine learning problem with a neural network mindset and using vectorization to speed up deep learning models. ➛ Built a neural network with one hidden layer using forwardpropagation and backpropagation. ➛ Learned the key computations underlying deep learning, used them to build and train deep neural networks, and apply them to computer vision. #CNN #Deeplearning #ComputerVision #OpenCV #TensorFlow #Keras #neuralnetworks #machinelearning #research #ai #python

I'm happy to share that I have completed Course 1 of 5 in the Deep Learning Specialization: Neural Networks and Deep Learning! 🧠 This course, led by Andrew Ng and offered through DeepLearning.AI, provided a deep dive into the fundamentals of neural networks, including building and training models. For my course project, I had to build a logistic regression model to predict cat images using ReLU and Sigmoid activation functions - an exciting challenge that solidified my understanding of deep learning concepts. Stay tuned for more updates as I continue this specialization journey!

🚀 Excited to share that I've just completed the "Introduction to Deep Learning and Neural Networks with Keras" course authorized by IBM! 📚 This comprehensive course was divided into 5 modules, covering a range of fascinating topics and essential concepts, including: - Artificial Neural Networks - Classification Models using Keras - Regression Models - Convolutional Neural Networks (CNNs) - A hands-on course project For the course project, I had the opportunity to build a regression model in Keras based on data provided in a previous lab. This involved experimenting with various parameters, such as increasing the number of training epochs and adjusting the number of hidden layers, to understand their impact on model performance. This practical experience not only deepened my understanding of the theoretical aspects but also allowed me to see firsthand how different configurations can influence the outcomes in deep learning models. I'm thrilled about the knowledge and skills I've gained from this course and look forward to applying them in future projects. This journey has definitely fueled my passion for deep learning and artificial intelligence! 🌟 #DeepLearning #NeuralNetworks #Keras #MachineLearning #AI #IBM #ContinuousLearning #ProfessionalDevelopment